vertex-ai-endpoint-config
Vertex Ai Endpoint Config - Auto-activating skill for GCP Skills. Triggers on: vertex ai endpoint config, vertex ai endpoint config Part of the GCP Skills skill category.
36
3%
Does it follow best practices?
Impact
99%
1.03xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/14-gcp-skills/vertex-ai-endpoint-config/SKILL.mdQuality
Discovery
7%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a very weak description that essentially just restates the skill name without providing any meaningful information about capabilities, actions, or usage triggers. It reads as auto-generated boilerplate with no substantive content. The repeated trigger term and lack of concrete actions make it nearly useless for skill selection among a large set of skills.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Configures Vertex AI endpoints including deploying models, setting traffic splits, configuring autoscaling policies, and managing endpoint resources.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user needs to deploy a model to a Vertex AI endpoint, configure prediction serving, set up traffic splitting, or manage online prediction infrastructure.'
Include natural keyword variations users might say, such as 'model deployment', 'online prediction', 'endpoint scaling', 'traffic split', 'serving config', and file/resource types like 'endpoint YAML' or 'gcloud ai endpoints'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions whatsoever. It only names 'Vertex AI Endpoint Config' without describing what it actually does (e.g., create endpoints, configure scaling, deploy models). 'Auto-activating skill for GCP Skills' is vague filler. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name itself, and the 'when' clause is just a repeated trigger phrase with no meaningful guidance. There is no explicit 'Use when...' clause with actionable triggers. | 1 / 3 |
Trigger Term Quality | The trigger terms are just 'vertex ai endpoint config' repeated twice. Missing natural variations users would say like 'deploy model endpoint', 'endpoint scaling', 'Vertex AI serving', 'model deployment', 'online prediction', or 'endpoint traffic split'. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'Vertex AI Endpoint Config' is somewhat specific to a particular GCP service, which provides some distinctiveness. However, it could overlap with other Vertex AI or GCP deployment skills since no specific actions are delineated. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is a hollow template with no actual content about Vertex AI endpoint configuration. It contains no code, no commands, no specific GCP concepts, and no actionable guidance whatsoever. It merely restates its own trigger phrase in various ways across every section.
Suggestions
Add concrete, executable code examples showing how to configure a Vertex AI endpoint (e.g., using gcloud CLI commands or Terraform/Python SDK snippets for deploying a model to an endpoint).
Define a clear multi-step workflow for endpoint configuration: create endpoint, deploy model, configure traffic split, validate with a prediction request.
Include specific configuration parameters and their recommended values (e.g., machine type, min/max replicas, traffic split percentages, logging settings).
Remove all meta-description sections ('When to Use', 'Example Triggers', 'Capabilities') and replace with actual technical content that teaches Claude how to perform the task.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely filler with no substantive information. It explains what the skill does in abstract terms without providing any actual guidance on Vertex AI endpoint configuration. Every section restates the same vague idea. | 1 / 3 |
Actionability | There are zero concrete commands, code examples, API calls, or specific configuration steps. The content only describes what it could do rather than providing any executable or actionable guidance. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, no validation checkpoints—just vague claims like 'provides step-by-step guidance' without actually providing any. | 1 / 3 |
Progressive Disclosure | No references to detailed files, no structured navigation, and no meaningful content organization. The sections are superficial headers over repetitive placeholder text. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
4dee593
- Reviewed
Table of Contents
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